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5 ways to deploy your own large language model

CIO

A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities. Vector databases and RAG For most companies looking to customize their LLMs, retrieval augmented generation (RAG) is the way to go.

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Valued at $1B, Kai-Fu Lee’s LLM startup unveils open source model

TechCrunch

Kai-Fu Lee, the computer scientist known in the West for his bestseller AI Superpowers and in China for his bets on artificial intelligence unicorns, has a new venture — and a great ambition. AI with the vision to develop a homegrown large language model for the Chinese market. […] © 2023 TechCrunch.

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SAP names Philipp Herzig as chief artificial intelligence officer

CIO

Philipp Herzig, formerly head of cross-product engineering and experience, now leads a new “end-to-end growth area” focused on AI as the company’s chief artificial intelligence officer (CAIO). With this new structure, SAP aims to accelerate the pace of its AI development, according to a statement from the software manufacturer.

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Article: Software Testing, Artificial Intelligence and Machine Learning Trends in 2023

InfoQ Culture Methods

Technology has taken significant leaps within the last few years, introducing advancements that have taken us further into the digital age — impacting the software testing industry and we're seeing advances in machine learning, artificial intelligence, and the neural networks making them possible. By Adam Sandman

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.

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Building a vision for real-time artificial intelligence

CIO

Data is a key component when it comes to making accurate and timely recommendations and decisions in real time, particularly when organizations try to implement real-time artificial intelligence. The underpinning architecture needs to include event-streaming technology, high-performing databases, and machine learning feature stores.

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How AI is reshaping Saudi Aramco’s oil exploration and underwater operations strategy

CIO

Saudi Aramco is spearheading the innovations by embracing cutting-edge technologies like artificial intelligence, both within its core operations and beyond, which places the company ahead of the curve. USD billion in 2023, representing a 15% annual increase despite global challenges.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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Building User-Centric and Responsible Generative AI Products

Speaker: Shyvee Shi - Product Lead and Learning Instructor at LinkedIn

In the rapidly evolving landscape of artificial intelligence, Generative AI products stand at the cutting edge. This presentation unveils a comprehensive 7-step framework designed to navigate the complexities of developing, launching, and scaling Generative AI products.